title: Knowledge-based analysis and understanding of medical images.
abstract: Knowledge-based image analysis and interpretation of radiological images is of significant interest for several reasons including a means to identify and label each part of the image for further automated diagnostic analysis. Also, there is a need to develop a knowledge-based biomedical image analysis system which can analyze and interpret the anatomical images (such as those obtained from X-ray computed tomography (CT) scanning) in order to help analysis of functional images (such as those obtained from positron emission tomography (PET) scanning) of the organ of the same patient. This paper deals with the design and implementation of a knowledge-based system to analyze and interpret CT anatomical images of the human chest. In the approach presented here, the emphasis has been on the development of a strong low-level analysis system with the capability of analyzing in both bottom-up and top-down modes; and on the use of hierarchical relational, spatial, and structural knowledge of human anatomy in the process of high-level analysis and recognition.
authors.affiliation: Department of Electrical and Computer Engineering, University of Cincinnati, OH 45221.
authors.forename: A P
authors.initials: AP
authors.lastname: Dhawan
authors.forename: S
authors.initials: S
authors.lastname: Juvvadi
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D011856:Radiographic Image Enhancement / Q000379:methods; D013902:Radiography, Thoracic; D012016:Reference Values; D014055:Tomography, Emission-Computed / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000379:methods